Discrete time signals

In this chapter, the following content will be discussed: Discrete – time signals, discrete – time systems, convolution description of linear time – invariant systems, properties of linear time – invariant systems, analytic evaluation of convolution, numerical computation of convolution, real – time implementation of FIR filters,...

A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing.
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Lecture Digital signal processing - Lecture 1 introduction, discrete-time signals and systems. After completing this chapter, students will be able: To make the students able to apply digital filters according to known filter specifications, to provide the knowledge about the principles behind the discrete Fourier transform (DFT) and its fast computation,...

(BQ) Part 2 book "Signals and systems using MATLAB" has contents: Sampling theory, Discrete-Time signals and systems, The Z-Transform, fourier analysis of discrete time signals and systems, introduction to the design of discrete filters, applications of discrete time signals and systems

Chapter 3 presents the discrete-time systems. In this chapter, you will learn to: Input/output relationship of the systems, linear time-invariant (LTI) systems, FIR and IIR filters, causality and stability of the systems.

Lecture Signal processing: Fourier representation of signals include all of the following content: Sinusoidal signals and their properties, fourier representation of continuous – time signals, fourier representation of discrete – time signals, summary of fourier series and fourier transforms, properties of the discrete – time fourier transform.

Lecture Signal processing: Sampling of continuous – Time signals include all of the following content: Ideal periodic sampling of continous – time signals, reconstruction of a bandlimited signal from its samples, the effect of undersampling: aliasing, discrete – time processing of continuous – time signals, practical sampling and reconstruction, sampling of bandpass signals.

Digital signal processing (DSP) is concerned with the representation of signals as a sequence
of numbers and the algorithmic operations carried out on the signals to extract specific
information contained in them. In barely 40 years the field of digital signal processing has
matured considerably due to the phenomenal growth in both research and applications, and
almost every university is now offering at least one or more courses at the upper division
and/or first-year graduate level on this subject. ...

This authoritative book, highly regarded for its intellectual quality and contributions provides a solid foundation and life-long reference for anyone studying the most important methods of modern signal and system analysis. The major changes of the revision are reorganization of chapter material and the addition of a much wider range of difficulties.

Discrete wavelet transform (DWT) algorithms have become standard tools for discrete-time signal and image processing in several areas in research and industry. As DWT provides both frequency and location information of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Theory and Applications describes the latest progress in DWT analysis in non-stationary signal processing, multi-scale image enhancement as well as in biomedical and industrial applications....

After studying this chapter students will be able to understand frequency analysis of signals and systems. This chapter includes content: Discrete time fourier transform DTFT, discrete fourier transform DFT, fast fourier transform FFT.

The main contents of this chapter include all of the following: Direct computation of the DFT, decimation-in-time FFT algorithms, decimation-in-frequency FFT algorithms, fourier analysis of signals using the DFT.

Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications.